Stephan Stephany

Identification of inherent optical properties and bioluminescence source term in a hydrologic optics problem

Abstract The estimation of the pair absorption–scattering of inherent optical properties (IOPs) and the bioluminescent source profile in natural waters is achieved from in situ irradiance data. This inverse problem is formulated as a nonlinear constrained optimization problem, assuming constant IOPs and that the unknown bioluminescent profile can be represented by a sum of distributed Gaussian sources. The objective function is defined as the squared Euclidean norm of the difference vector between experimental and computed data. The Hydrolight code, based on the invariant imbedding theory, is used for the direct problem. The methodology yielded good results using synthetic data for the joint estimation of IOPs and bioluminescence, performed in an alternate, step-by-step manner.

Inverse problems in space science and technology

Solutions for inverse problems appearing in space applications and space technology are described. The inverse problem is formulated as a nonlinear optimization problem. Usually some additional information must be added from our previous knowledge about the physical phenomenon. In general this a priori information means smoothness, in other words, regularized solutions are searched for. The methodology is applied to geophysics (magneto-telluric inversion), meteorology (temperature retrieval from satellite data), and oceanography (inverse hydrologic optics), as examples of space applications. The scheme is also employed for solving an inverse problem emerging from technology: the inverse design of a space radiator.

Fuzzy ant colony optimization for estimating chlorophyll concentration profile in offshore sea water

The determination of some inherent optical properties can be addressed by estimating the ocean chlorophyll concentration, if bio-optical models can be applied – such as for the offshore sea water. This inverse problem can be formulated as an optimization problem and iteratively solved, where the radiative transfer equation is the direct model. An objective function is given by the square difference between computed and in situ experimental radiances at every iteration. In the standard ant colony optimization (ACO), the pheromone is reinforced only on the best ant of the population. The fuzzy strategy consists in including additional pheromone quantity on the best ant, but a small pheromone quantity is also spread over the other solutions close to the best one. Test results show that the fuzzy-ACO produces better inverse solutions.

A new classification approach for detecting severe weather patterns

Abstract Early detection of possible occurrences of severe convective events would be useful in order to avoid, or at least mitigate, the environmental and socio-economic damages caused by such events. However, the enormous volume of meteorological data currently available makes difficult, if not impossible, its analysis by meteorologists. In addition, severe convective events may occur in very different spatial and temporal scales, precluding their early and accurate prediction. In this work, we propose an innovative approach for the classification of meteorological data based on the frequency of occurrence of the values of different variables provided by a weather forecast model. It is possible to identify patterns that may be associated to severe convective activity. In the considered classification problem, the information attributes are variables outputted by the weather forecast model Eta, while the decision attribute is given by the density of occurrence of cloud-to-ground atmospheric electrical discharges, assumed as correlated to the level of convective activity. Results show good classification performance for some selected mini-regions of Brazil during the summer of 2007. We expect that the screening of the outputs of the meteorological model Eta by the proposed classifier could serve as a support tool for meteorologists in order to identify in advance patterns associated to severe convective events.

Processing Mesoscale Climatology in a Grid Environment

Enhancing the quality of weather and climate forecasts are central scientific research objectives worldwide. However, simulations of the atmosphere, usually demand high processing power and large storage resources. In this context, we present the GBRAMS project, that applies grid computing to speed up the generation of a regional model climatology for Brazil. A grid infrastructure was built to perform long-term integrations of a mesoscale numerical model (BRAMS), managing a queue of up to nine independent jobs submitted to three clusters spread over Brazil- Three distinct middlewares, Globus Toolkit, OurGrid and OAR/CIGRI, were compared in their ability to manage these jobs, and results on the usage of each node of the grid are provided. We analyze the impact of the resulted climatology in the accuracy of climate forecast, showing model bias removal which indicates correctness of the generated climatology. Our central contribution are how to use grid computing to speed-up climatology generation and the middleware impact on this enterprise.

Interpolating EFGM for computing continuous and discontinuous electromagnetic fields

Purpose – This paper proposes an interpolating approach of the element‐free Galerkin method (EFGM) coupled with a modified truncation scheme for solving Poissons boundary value problems in domains involving material non‐homogeneities. The suitability and efficiency of the proposed implementation are evaluated for a given set of test cases of electrostatic field in domains involving different material interfaces.Design/methodology/approach – The authors combined an interpolating approximation with a modified domain truncation scheme, which avoids additional techniques for enforcing the Dirichlet boundary conditions and for dealing with material interfaces usually employed in meshfree formulations.Findings – The local electric potential and field distributions were correctly described as well as the global quantities like the total potency and resistance. Since, the treatment of the material interfaces becomes practically the same for both the finite element method (FEM) and the proposed EFGM, FEM‐oriented...

Reconstruction of vertical profiles of the absorption and scattering coefficients from multispectral radiances

An inverse hydrologic optics problem is solved using a recent intrinsic regularization scheme that is coupled to a standard Ant Colony System (ACS). The regularization scheme pre-selects candidate solutions based on their smoothness, quantified by a Tikhonov norm. The Chlorophyll profile is reconstructed from upwelling radiance experimental measurements in the ocean water using 10 wavelengths (multispectral approach) and upward polar directions. Vertical profiles of the absorption and scattering coefficients are estimated from the Chlorophyll profile by means of bio-optical models. The inverse problem is formulated as an optimization problem and iteratively solved by an ACS using the radiative transfer equation as direct model. An objective function is given by the square difference between computed and experimental radiances at every iteration. Each candidate solution corresponds to a discrete Chlorophyll profile. The radiative transfer equation is solved using the Laplace transform discrete ordinate (LTSN) method. A parallel implementation of the Ant Colony System is used and executed in a distributed memory machine.

A parallel implementation of the LTSn method for a radiative transfer problem

A radiative transfer solver that implements the LTSn method was optimized and parallelized using the MPI message passing communication library. Timing and profiling information was obtained for the sequential code in order to identify performance bottlenecks. Performance tests were executed in a distributed memory parallel machine, a multicomputer based on IA-32 architecture. The radiative transfer equation was solved for a cloud test case to evaluate the parallel performance of the LTSn method. The LTSn code includes spatial discretization of the domain and Fourier decomposition of the radiances leading to independent azimuthal modes. This yields an independent radiative transfer equation for each mode that can be executed by a different processor in a parallel implementation. Speed-up results show that the parallel implementation is suitable for the used architecture.

A research agenda for iterative approaches to inverse problems using evolutionary computation

We address the relevance of evolutionary computation for iterative approaches to inverse problems. We focus on a set of six real-world problems selected from the areas of space dynamics, materials science, geophysics, heat transfer, oceanography and meteorology. These problems are far from being trivial and their associated direct models yield a wide structural diversity, thus providing a rich sample of the space of inverse problems. We neither discuss any particular problem in depth, nor present any results obtained so far. Our emphasis is on the research agenda defined by them, for the issue of deriving a generic methodology for approaching inverse problems that has evolutionary computation in its core.

A Knowledge-Based and Model-Driven Requirements Engineering Approach to Conceptual Satellite Design

Satellite systems are becoming even more complex, making technical issues a significant cost driver. The increasing complexity of these systems makes requirements engineering activities both more important and difficult. Additionally, todays competitive pressures and other market forces drive manufacturing companies to improve the efficiency with which they design and manufacture space products and systems. This imposes a heavy burden on systems-of-systems engineering skills and particularly on requirements engineering which is an important phase in a systems life cycle. When this is poorly performed, various problems may occur, such as failures, cost overruns and delays. One solution is to underpin the preliminary conceptual satellite design with computer-based information reuse and integration to deal with the interdisciplinary nature of this problem domain. This can be attained by taking a model-driven engineering approach (MDE), in which models are the main artifacts during system development. MDE is an emergent approach that tries to address system complexity by the intense use of models. This work outlines the use of SysML (Systems Modeling Language) and a novel knowledge-based software tool, named SatBudgets, to deal with these and other challenges confronted during the conceptual phase of a university satellite system, called ITASAT, currently being developed by INPE and some Brazilian universities.